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R. Meneghini and J. A. Jones

Abstract

Estimates of rain rate derived from a spaceborne weather radar will be most reliable over an intermediate range of values. At light or heavy rain rates, where the signal-to-noise ratios are degraded either by small values of the backscattered power or by large attenuation, the accuracy will be poor. In forming an area average of the rain rate, an alternative to the averaging of the high-resolution estimates, irrespective of their individual accuracies, is a multiple threshold approach. The method is based on the fact that the Fractional area above a particular rain-rate threshold Rj is related to the cumulative distribution of rain rates evaluated at Rj. Varying the threshold over the effective dynamic range of the radar yields the cumulative distribution function over this range. To obtain the distribution at all rain rates, a lognormal or gamma test function is selected such that the mean-square error between the test function and the measured values is minimized. Once the unknown parameters are determined, the first-order statistics of the areawide rain-rate distribution can be found. Tests of the method with data from the SPANDAR radar provide comparisons between it and the single threshold and the direct averaging approaches.

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P. D. Jones and A. Moberg

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This study is an extensive revision of the Climatic Research Unit (CRU) land station temperature database that is used to produce a gridbox dataset of 5° latitude × 5° longitude temperature anomalies. The new database comprises 5159 station records, of which 4167 have enough data for the 1961–90 period to calculate or estimate the necessary averages. Apart from the increase in station numbers compared to the earlier study in 1994, many station records have had their data replaced by newly homogenized series that have been produced by several recent studies. New versions of all the gridded datasets currently available on the CRU Web site (http://www.cru.uea.ac.uk) have been developed. This includes combinations with marine (sea surface temperature anomalies) data over the oceans and versions with adjustment of the variance of individual gridbox series to remove the effects of changing station numbers through time.

Hemispheric and global temperature averages for land areas developed with the new dataset differ slightly from those developed in 1994. Possible reasons for the differences between the new and the earlier analysis and those from the National Climatic Data Center and the Goddard Institute for Space Studies are discussed. Differences are greatest over the Southern Hemisphere and at the beginnings and ends of each time series and relate to gridbox sizes and data availability. The rate of annual warming for global land areas over the 1901–2000 period is estimated by least squares to be 0.07°C decade−1 (significant at better than the 99.9% level). Warming is not continuous but occurs principally over two periods (about 1920–45 and since 1975). Annual temperature series for the seven continents and the Arctic all show significant warming over the twentieth century, with significant (95%) warming for 1920–44 for North America, the Arctic, Africa, and South America, and all continents except Australia and the Antarctic since 1977. Cooling is significant during the intervening period (1945–76) for North America, the Arctic, and Africa.

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Lawrence A. Dean and Douglas M. A. Jones

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No Abstract Available

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DOUGLAS M. A. JONES and FLOYD A. HUFF

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No Abstract Available.

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Thomas A. Jones and Sundar A. Christopher
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P. A. Jones and A. Henderson-Sellers

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Historical records of mean monthly cloud amount over Australia have been studied to determine whether there is any long-term trend. Of 318 stations with more than 30 years of data, 252 show an increase and 66 a decrease. The cloud amount shows a rise of 5% between 1910 and 1989, when averaged over all stations. The trend is not uniform, however, with a slight fall in cloud between 1910 and 1930 and with most of the rise between 1930 and 1980. Sunshine records were used to check the cloud record for systematic errors. Monthly average cloud and sunshine fractions are correlated with coefficient r=−0.87 and with best-fit slope −1.00. The sum of cloud and sunshine fractions is around 1.2, whereas it may be expected that the sun should be 1.0 if the cloud and sunshine fractions are complementary. The sunshine and cloud variations are in close agreement for the period 1950 to 1989. The subset of stations that have sunshine records shows no overall change in cloudiness or sunshine over this period, with 31 stations showing an increase in cloud and 28 a decrease. An independent dataset of 41 stations, mostly airports, shows no significant trend over the period from 1940 to 1988, with 24 stations showing a decrease in cloud and only 17 showing an increase over this period. It is suggested that there is an overall long-term increase in total cloud amount over Australia, but that it does not occur uniformly for all stations, so that some groups of stations show no increase. However, the overall trend must remain tentative until the reason for the differences between the datasets is clarified.

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Thomas A. Jones and Sundar A. Christopher

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Many large grass fires occurred in north Texas and southern Oklahoma on 9 April 2009, destroying hundreds of homes and businesses and burning thousands of acres of grasslands, producing large smoke and debris plumes that were visible from various remote sensing platforms. At the same time, strong westerly winds were transporting large amounts of dust into the region, mixing with the smoke and debris already being generated. This research uses surface- and satellite-based remote sensing observations of this event to assess the locations of fires and the spatial distribution of smoke and dust aerosols. The authors present a unique perspective by analyzing radar observations of fire debris in conjunction with the satellite analysis of submicrometer smoke aerosol particles. Satellite data clearly show the location of the individual fires and the downwind smoke plumes as well as the large dust storm present over the region. In particular, Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical thickness at 0.55 μm within the dust plume was around 0.5, and it increased to greater than 1.0 when combined with smoke. Using the difference in 11- versus 12-μm brightness temperature data combined with surface observations, the large extent of the dust plume was evident through much of north-central Texas, where visibilities were low and the 11–12-μm brightness temperature difference was negative. Conversely, smoke plumes were characterized by higher reflectance at 0.6 μm (visible wavelength). Cross sections of radar data through the several smoke and debris plumes indicated the burnt debris reached up to 5 km into the atmosphere. Plume height output from modified severe storm algorithms produced similar values. Since smoke aerosols are smaller and lighter when compared with the debris, they were likely being transported even higher into the atmosphere. These results show that the combination of satellite and radar data offers a unique perspective on observing the characteristics and evolution of smoke and debris plume emanating from grass fire events.

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A. Bodas-Salcedo, M. A. Ringer, and A. Jones

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The partitioning of the earth radiation budget (ERB) between its atmosphere and surface components is of crucial interest in climate studies as it has a significant role in the oceanic and atmospheric general circulation. An analysis of the present-day climate simulation of the surface radiation budget in the atmospheric component of the new Hadley Centre Global Environmental Model version 1 (HadGEM1) is presented, and the simulations are assessed by comparing the results with fluxes derived from satellite data from the International Satellite Cloud Climatology Project (ISCCP) and ground measurements from the Baseline Surface Radiation Network (BSRN).

Comparisons against radiative fluxes from satellite and ground observations show that the model tends to overestimate the surface incoming solar radiation (Ss,d). The model simulates Ss,d very well over the polar regions. Consistency in the comparisons against BSRN and ISCCP-FD suggests that the ISCCP-FD database is a good test for the performance of the surface downwelling solar radiation in climate model simulations. Overall, the simulation of downward longwave radiation is closer to observations than its shortwave counterpart. The model underestimates the downward longwave radiation with respect to BSRN measurements by 6.0 W m−2.

Comparisons of land surface albedo from the model and estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) show that HadGEM1 overestimates the land surface albedo over deserts and over midlatitude landmasses in the Northern Hemisphere in January. Analysis of the seasonal cycle of the land surface albedo in different regions shows that the amplitude and phase of the seasonal cycle are not well represented in the model, although a more extensive validation needs to be carried out.

Two decades of coupled model simulations of the twentieth-century climate are used to look into the model’s simulation of global dimming/brightening. The model results are in line with the conclusions of the studies that suggest that global dimming is far from being a uniform phenomenon across the globe.

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Roland A. Madden and Richard H. Jones

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No abstract available.

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Thomas A. Jones and Daniel J. Cecil

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Three hurricanes, Claudette (2003), Isabel (2003), and Dora (1999), were selected to examine the Statistical Hurricane Intensity Prediction Scheme with Microwave Imagery (SHIPS-MI) forecast accuracy for three particular storm types. This research was conducted using model analyses and tropical cyclone best-track data, with forecasts generated from a dependent sample. The model analyses and best-track data are assumed to be a “perfect” representation of the actual event (e.g., perfect prog assumption). Analysis of intensity change forecasts indicated that SHIPS-MI performed best, compared to operational SHIPS output, for tropical cyclones that were intensifying from tropical storm to hurricane intensity. Passive microwave imagery, which is sensitive to the intensity and coverage of precipitation, improved intensity forecasts during these periods with a positive intensity change contribution resulting from above normal inner-core precipitation. Forecast improvement was greatest for 12–36-h forecasts, where the microwave contribution to SHIPS-MI was greatest. Once a storm reached an intensity close to its maximum potential intensity, as in the case of Isabel and Dora, both SHIPS and SHIPS-MI incorrectly forecast substantial weakening despite the positive contribution from microwave data. At least in Dora’s case, SHIPS-MI forecasts were slightly stronger than those of SHIPS. Other important contributions to SHIPS-MI forecasts were examined to determine their importance relative to the microwave inputs. Inputs related to sea surface temperature (SST) and persistence–climatology proved to be very important to intensity change forecasts, as expected. These predictors were the primary factor leading to the persistent weakening forecasts made by both models for Isabel and Dora. For Atlantic storms (Claudette and Isabel), the contribution from shear also proved important at characterizing the conduciveness of the environment toward intensification. However, the shear contribution was often small as a result of multiple offsetting shear-related predictors. Finally, it was observed that atmospheric parameters not included in SHIPS, such as eddy momentum flux, could substantially affect the intensity, leading to large forecast errors. This was especially true for the Claudette intensity change forecasts throughout its life cycle.

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